T. E. Peto

This paper predicts pyrazinamide resistance in Mycobacterium tuberculosis using machine learning models trained on pncA mutations and structural features, achieving 80.2% sensitivity and 76.9% specificity.

This study evaluates four AMR gene typing methods using simulated and real E. coli data, revealing significant discrepancies and highlighting issues with current bioinformatic approaches.

BashTheBug uses crowdsourced volunteers to accurately measure MICs of 13 antitubercular drugs from microdilution plates, showing median/mode of classifications is sufficient.

The paper shows hospital sink drains are colonized by diverse E. coli and Klebsiella strains, including resistant ones, and may contribute to patient infections.

This paper develops a thermo-protection buffer to enable direct whole genome sequencing of Mycobacteria from clinical samples using Nanopore technology, achieving high coverage at low bacterial concentrations.

This study shows that amoxicillin-clavulanate resistance in E. coli is quantitative, not binary, and that WGS-based predictions outperform traditional phenotyping methods.

This paper introduces hash-cgMLST, a method for rapid genome comparison in Clostridium difficile, showing it matches standard cgMLST performance but with faster processing.

This study develops a hybrid protocol combining culture enrichment and plasmid extraction to improve detection of antimicrobial resistance genes in faecal samples.

The paper validates a 14-drug microtitre plate for measuring MICs of anti-TB compounds in M. tuberculosis isolates, finding optimal reading with the Vizion system after 14 days incubation.

This paper introduces AMyGDA, a software tool for automated detection of M. tuberculosis growth on 96-well plates to determine drug susceptibility.

The paper investigates the evolutionary history of Clostridium difficile RT078, finding that tetracycline resistance genes, particularly tetM, were acquired independently in multiple clonal expansions, contributing to its increased prevalence.

The paper identifies genomic regions in Mycobacterium tuberculosis that contribute to artefactual variation in bacterial similarity searches and proposes a method to reduce such variation.

This paper develops a low-cost WGS method for TB diagnosis and surveillance using direct respiratory samples, achieving rapid results with high concordance with reference labs.